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What is pandas?

Pandas is a versatile open-source library for data analysis and manipulation that excels in speed and power while maintaining a user-friendly interface within the Python ecosystem. It supports a wide range of data formats for both importing and exporting, such as CSV, text documents, Microsoft Excel, SQL databases, and the efficient HDF5 format. The library stands out with its intelligent data alignment features and its adept handling of missing values, allowing for seamless label-based alignment during calculations, which greatly aids in the organization of chaotic datasets. Moreover, pandas includes a sophisticated group-by engine that facilitates complex aggregation and transformation tasks, making it simple for users to execute split-apply-combine operations on their data. In addition to these capabilities, pandas is equipped with extensive time series functions that allow for the creation of date ranges, frequency conversions, and moving window statistics, as well as managing date shifting and lagging. Users also have the flexibility to define custom time offsets for specific applications and merge time series data without losing any critical information. Ultimately, the comprehensive array of features offered by pandas solidifies its status as an indispensable resource for data professionals utilizing Python, ensuring they can efficiently handle a diverse range of data-related tasks.

What is Matplotlib?

Matplotlib is a flexible library that facilitates the creation of static, animated, and interactive graphs in Python. It not only makes it easy to generate simple plots but also supports the development of intricate visualizations. A wide range of third-party extensions further amplifies Matplotlib's functionality, offering sophisticated plotting interfaces like Seaborn, HoloViews, and ggplot, as well as mapping and projection tools such as Cartopy. This rich ecosystem empowers users to customize their visual outputs according to individual requirements and tastes. Additionally, the continuous growth of the community around Matplotlib ensures that innovative features and improvements are regularly introduced, enhancing the overall user experience.

Media

Media

Integrations Supported

Dash
Kedro
MLJAR Studio
Train in Data
Yandex Data Proc
Amazon SageMaker Data Wrangler
ApertureDB
Avanzai
Cleanlab
Coiled
Daft
DagsHub
Flyte
Giskard
Python
RunCode
TeamStation
Union Pandera
scikit-learn

Integrations Supported

Dash
Kedro
MLJAR Studio
Train in Data
Yandex Data Proc
Amazon SageMaker Data Wrangler
ApertureDB
Avanzai
Cleanlab
Coiled
Daft
DagsHub
Flyte
Giskard
Python
RunCode
TeamStation
Union Pandera
scikit-learn

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

pandas

Date Founded

2008

Company Website

pandas.pydata.org

Company Facts

Organization Name

Matplotlib

Company Website

matplotlib.org

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Categories and Features

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

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